Increasing global energy demands, depletion of low extraction-cost fossil fuel reserves, and environmental concerns are driving forces for the search for renewable and environmentally friendly energy sources. Bioethanol is among the leading alternatives to petroleum-derived fossil fuels for the transportation sector given that it is compatible with current engine technologies, burns cleaner than gasoline, has a high octane/cetane number, and can be derived from renewable biomass feedstocks (Arora et al., 2015. Renew Sust Energ Rev. 51, 699-717; Vohra et al., 2014. J. of Env. Chem. Eng. 2, 573-584). The USA and Brazil are among the leaders in ethanol production, generating 14.8 and 7.1 billions of gallons of ethanol in 2015, respectively. Of the total global bioethanol produced, roughly 50% is derived from maize and 30% is derived from sugarcane. This dependence of bioethanol production on food/feed crops may increase food costs and increases the volatility of ethanol prices (Vohra et al., 2014. J. of Env. Chem. Eng. 2, 573-584). Life cycle analysis has further shown that substituting gasoline with cellulosic ethanol can reduced greenhouse gas emission by up to 115%, versus a 19-48% reduction with corn ethanol (Wang et al., 2012. Environ Res Lett. 7). Thus, a transition to lignocellulosic feedstocks for bioethanol production is needed.
Currently, bioethanol is predominantly made via fermentation of mono- or disaccharides using Saccharomyces cerevisiae or Zymomonas mobilis. While these organisms are capable of high ethanol yields and titers, they cannot natively deconstruct highly recalcitrant lignocellulosic biomass to liberate fermentable sugars (Himmel et al., 2007. Abstr Pap Am Chem S. 233). Thus, lignocellulosic bioethanol production using these organisms requires chemical and/or enzymatic hydrolysis of lignocellulosic biomass, separate cellulase production, and subsequent fermentation, increasing production costs. Alternatively, a number of organisms are capable of cellulase-mediated cellulose hydrolysis and subsequent fermentation to ethanol via consolidated bioprocessing (CBP), potentially allowing for enhanced process economics (Lynd et al., 2005. Curr. Op. in Biotech. 16, 577-83; Lynd et al., 2002. Microbio. and Mol. Bio. Rev. 66, 506-77). However, to date, none can produce ethanol at yields and titers sufficient for economic viability.
Clostridium thermocellum is a promising candidate for lignocellulosic bioethanol production via CBP because it has the innate ability to rapidly solubilize raw biomass with minimal or no pre-treatment (Paye et al., 2016. Biotech. for Biofuels. 9), and ferment resulting cellulosic hydrolysis products into ethanol. However, due to branched product pathways that divert carbon and electrons to products other than ethanol, wild type C. thermocellum ethanol yields are approximately 30% of the theoretical maximum of 2 moles ethanol per mole hexose, well below industrial requirement of approximately 90%. The remaining carbon is used to produce canonical fermentation products (acetate, lactate, formate, and H2) as well as secreted amino acids (primarily valine and alanine) (Ellis et al., 2012. Bioresource Technol. 103, 293-9; Kridelbaugh et al., 2013. Bioresource Technol. 130, 125-135; van der Veen et al., 2013. J Ind Microbiol Biot. 40, 725-34) and other compounds including pyruvate, malate, fumarate, isobutanol, and butanediol (Holwerda et al., 2014. J Ind Microbiol Biot. 39, 943-947), further limiting ethanol yields. Elucidation of metabolic pathways via enzymology (Carere et al., 2014. Appl Microbiol Biotechnol. 98, 2829-40; Lamed and Zeikus, 1980. J BacterioL 144, 569-78; Lin et al., 1998; Özkan, 2004. Can. J. of Microbiol. 50, 845-851; Rydzak et al., 2009. Journal of Biotechnology. 140, 169-75; Sparling et al., 2006. Can J Microbiol. 52, 681-8; Taillefer et al., 2015. Appl Environ Microb. 81, 2423-2432; Zhou et al., 2013), transcriptomics (Carere et al., 2014. Appl Microbiol Biotechnol. 98, 2829-40; Deng et al., 2013. Metab Eng. 15, 151-8; Raman et al., 2011. BMC Microbiol. 11, 134; Wilson et al., 2013. Biotechnology for Biofuels. 6, 131; Yang et al., 2012. BMC Genomics. 13, 336), proteomics (Raman et al., 2009. PloS One. 4, e5271; Rydzak et al., 2014. Microbiol Biotechnol. 98, 6497-510; Rydzak et al., 2012. BMC Microbiology. 12, 214), and genetics (Argyros et al., 2011. Appl Environ Microb. 77, 8288-8294; Biswas et al., 2014. PloS one. 9, e86389; Biswas et al., 2015. Biotechnology for Biofuels.; Deng et al., 2013. Metab Eng. 15, 151-8; Tripathi et al., 2010. Appl Environ Microb. 76, 6591-9), in conjunction with improvements in C. thermocellum electrotransformation protocols (Olson and Lynd, 2012. Methods in Enzymology. 510, 317-30; Tyurin et al., 2004. Appl Environ Microbiol. 70, 883-90), transformation efficiencies (Guss et al., 2012. Biotechnology for biofuels. 5, 30), and gene deletion screening methods (Argyros et al., 2011. Appl Environ Microb. 77, 8288-8294; Tripathi et al., 2010. Appl Environ Microb. 76, 6591-9), has allowed for rational metabolic engineering of C. thermocellum to improve ethanol yields by eliminating pathways that lead to canonical fermentation products. While deletion of phosphotransacetlylase (pta) (Tripathi et al., 2010. Appl Environ Microb. 76, 6591-9) and pyruvate:formate lyase (pfl) (Rydzak et al., 2015. J Ind Microbiol Biot. 42, 1263-1272) eliminated acetate and formate production, respectively, marginal impacts on ethanol production were observed. Alternatively, elimination of lactate, lactate and acetate, or H2 via deletion of lactate dehydrogenase (ldh) (Biswas et al., 2014. PloS One. 9, e86389), ldh and pta (Argyros et al., 2011. Appl Environ Microb. 77, 8288-8294; van der Veen et al., 2013. J Ind Microbiol Biot. 40, 725-34), or [FeFe] hydrogenase maturation factor (hydG) and [NiFe] Ech-type hydrogenase (ech) (Biswas et al., 2015. Biotechnology for Biofuels), respectively, improved ethanol production. While deletion of all but one of these genes (ech) in a single strain (ΔhydG Δpfl Δpta-ack Δldh; strain AG553) resulted in the highest ethanol yielding C. thermocellum strain to date (Papanek et al., 2015. Metab Eng. 32, 49-54), ethanol yields typically ranged from 50-70% of the theoretical maximum, which is still below the benchmark 90% ethanol yields achieved by Saccharomyces cerevisiae or Zymomonas mobilis. Recently strain AG553 was evolved to grow faster, resulting in a strain able to produce 25 g/L ethanol at 75% of the theoretical maximum yield (Tian et al., 2016. Biotechnology for Biofuels. 9).
Recent studies have demonstrated that secreted amino acids typically account for approximately 4-10% of total substrate consumed in wild type C. thermocellum, reaching as high as 17% in certain mutants (i.e. evolved Δldh Δpta strain), with valine and alanine accounting for the bulk of these amino acids (Ellis et al., 2012. Bioresource Technol. 103, 293-9; Holwerda et al., 2014. J Ind Microbiol Biot. 39, 943-947; Kridelbaugh et al., 2013. Bioresource Technol. 130, 125-135; van der Veen et al., 2013. J Ind Microbiol Biot. 40, 725-34). The extent of amino acid secretion has also been shown to be dependent on medium nitrogen content (Kridelbaugh et al., 2013. Bioresource Technol. 130, 125-135) and carbon loading (Holwerda et al., 2014, J Ind Microbiol Biot. 39, 943-947), and has been proposed to alleviate carbon and electron imbalances. While few studies have measured amino acid secretion in other cellulolytic organisms, free amino acids in Clostridium cellulolyticum fermentations medium have been reported to account for 15% and 6% of total carbon consumed on cellobiose and cellulose, respectively (Desvaux et al., 2001. Journal of Bacteriology. 183, 119-130; Desvaux et al., 2001. Appl Environ Microb. 67, 3837-3845; Desvaux et al., 2001. Microbiol-Sgm. 147, 1461-1471; Guedon et al., 1999, Journal of Bacteriology. 181, 3262-3269), demonstrating that amino acid secretion in cellulolytic bacteria is not exclusive to C. thermocellum. In C. cellulolyticum, 30-fold higher protein/DNA ratios in supernatants versus cell extracts suggest that cell lysis is not the cause of amino acids in the medium (Guedon et al., 1999. Journal of Bacteriology. 181, 3262-3269).
In most bacteria, ammonium assimilation typically occurs via glutamate dehydrogenase (GLDH) or through the combination of glutamine synthetase (GS) and glutamine-oxoglutarate aminotransferase/glutamate synthase (GOGAT). GLDH catalyzes the reductive amination of α-ketoglutarate to glutamate using NAD(P)H, typically under nitrogen-rich conditions (Shimizu, 2013. ISRN Biochem, 645983). Alternatively, under nitrogen-limited conditions, ATP-dependent GS aminates glutamate to glutamine, and NAD(P)H or ferredoxin-dependent GOGAT replenishes the glutamate pool using glutamine and α-ketoglutarate. GSs can be divided into four groups, including Type I GSs (˜450 aa in length) which are widely distributed among bacteria and archeabacteria, Type II GSs (˜360 aa) which are typically found in plants and some soil bacteria, Type III GSs (˜730 aa) which have been identified in anaerobic bacteria and cyanobacteria, and the enigmatic GlnT family of poorly characterized GSs (van Rooyen et al., 2011. Acta Cryst. Sec. F. Str. Bio. Cryst. Comm., 67, 358-363). Type I GSs can be further divided into Type Iα, typically found in the Firmicutes and the Archaea, and Type Iβ found in many other groups (Brown et al., 1994. J. Mol. Evol., 38, 566-576).
With the exception of one by Bogdahn and Kliener (1986. Arch Microbiol. 145, 159-161), little has been done to elucidate nitrogen assimilation in C. thermocellum. Enzyme activity studies showed high NADPH-dependent glutamate dehydrogenase (GLDH) and moderate glutamine synthetase (GS) activities, but failed to detect any NADH or NADPH-dependent glutamine-oxoglutarate aminotransferase/glutamate synthase (GOGAT) activity (Bogdahn and Kleiner, 1986. Arch Microbiol. 145, 159-161). While RNA-seq studies show variable expression of these genes, the Type I gs, gldh, and two of the five genes in a cluster containing putative gogat genes are typically expressed at high levels (Gowen and Fong, 2010. Biotechnol J. 5, 759-767; Wilson et al., 2013. Biotechnology for Biofuels. 6, 131).